#DataLiteracy – Why is it important to us all
This article shares thought leadership on what Data Literacy is and why it is important to us all. As we evolve the resources of the world evolve also. Change is a constant however the one that succeeds is the one that knows how to benefit from the change. Humans are the catalyst that augments the intelligence contained within the data by employing their knowledge and skills. Just as they have learned to refine and derive benefit from natural resources, their attention is now on data.
Digital transformation is everywhere and impacts us equally at home and at work. With the automation and digitisation of daily administration and machines, we as humans are having to redefine our roles. This is an exciting time to look at how your organisation can compete as your industry is consumed by all things digital.
For this change to succeed it does need to be enabled or augmented by us mortals. Therefore we need to invest in improving our ability to respond in the most appropriate way when confronted with new challenges that relate to data-driven decision making. Augmenting human interaction and intelligence as needed.
Setting #DataLiteracy KPIs
Setting #DataLiteracy KPIs for your organisation will enable smarter business decisions about its future direction. This will allow your organisation to acquire latent, measurable business value.
Gartner: A Data and Analytics Leader’s Guide to Data Literacy
Champion data literacy and teach data as a second language to enable data-driven business
Imagine an organisation where the marketing department speaks French, the product designers speak German, the analytics team speaks Spanish and no one speaks a second language. Even if the organisation was designed as an integrated digital business, communicating business value and why specific technologies matter would be impossible.
That’s essentially the malfunction that occurs within a data-driven business when there is no data literacy. Without data literacy it doesn’t matter if data and analytics offer immense business value and are a required component of digital business. If no one outside the department understands what is being said, there can be no effective data or analytics based communication or decision making.
By 2020, 50% of organisations will lack the AI and data literacy skills necessary to achieve business value.
“The prevalence of data and analytics capabilities, including artificial intelligence, requires creators and consumers to ‘speak data’ as a common language,” says Valerie Logan, Senior Director Analyst, Gartner. “Data and analytics leaders must champion workforce data literacy as an enabler of digital business and treat information as a second language.”
Data and analytics will continue to move towards being a core part of digital business, with data being recognised as an organisational asset. To adapt to this ongoing change, employees must have at least a basic understanding of conversations about data and have the ability and confidence to contribute to the discussion. Having the ability to “speak data” will become an integral aspect of most day-to-day jobs.
What is data literacy?
Gartner defines data literacy as the ability to read, write and communicate data in context, including an understanding of data sources and constructs, analytical methods and techniques applied — and the ability to describe the use case, application and resulting value.
This all boils down to a simple question, “Do you speak data?”
Data literacy is an underlying component of digital dexterity
The ability to communicate in a common data language with shared understanding is a core skill for a core technology. It is the difference between successfully deriving value from data and analytics and losing out to competitors who have already made it a core competency.
Furthermore, Digital dexterity is dependent upon data literacy. This is an employee’s ability and desire to use existing and emerging technology to drive better business outcomes, another important skill for digital business.
Why is data literacy important?
In Gartner’s Annual Chief Data Officer Survey poor data literacy is ranked as the chief data officer’s second-biggest internal roadblock to the success of their office. Gartner expects that, by 2020, 80% of organisations will initiate deliberate competency development in the field of data literacy to overcome extreme deficiencies. By 2020, 50% of organisations will lack sufficient AI and data literacy skills to achieve business value.
As organisations continue to become more data-driven, poor data literacy will become an inhibitor to growth.
Ask the right data and analytics questions
Data and analytics leaders are responsible for creating the narrative for data literacy, highlighting the business value that can be gained.
First, assess the data literacy at your organisation with these five questions:
- How many people in your business do you think can interpret straightforward statistical operations (such as correlations), or can judge averages?
- How many managers are able to construct a business case based on concrete, accurate, and relevant numbers?
- How many managers can explain the output of their systems or processes?
- How many data scientists can explain the output of their machine learning algorithms?
- How many of your customers can truly appreciate and internalise the essence of the data you share with them?
“Not only must organisations take steps to educate professionals who are involved in crafting data-driven solutions, products and services, they must also ensure those steps achieve the goal of teaching all relevant employees to speak data as their new second language, as well as developing and nurturing communities in which the language will flourish,” says Logan.
Establish a data literacy program
Second, look for areas where communication barriers are preventing data from being utilised to its full business potential. Conduct data literacy assessments to be used as a baseline, and in turn to identify gaps in fluency and understanding.
Data and analytics leaders and data teams must lead by example
When teaching groups about data, make sure it’s in a fun and open environment, and think outside the box for training ideas. Don’t focus solely on slides or presentations — use games, quizzes and other creative ways to teach. For more inspiration, refer to the book ‘Game Storming’ by Gray, Brown, and Macanufo.
Next, try a data literacy proof-of-concept workshop in an area where language gaps exist. Have participants describe real-life common use cases as well as a use case specific to the organisation. Capture the lessons learned and then repeat the exercise, ensuring that participants use others’ languages. Share the lessons with the other groups to aid in raising your organisation’s awareness and understanding of the literacy gap.
Finally, don’t forget that data and analytics leaders and data teams must lead by example. Ensure that teams use appropriate data language in all meetings when discussing business outcomes and in other business situations. This includes encouraging those that are less confident to utilise what they have learnt about data.
Champion data literacy and evangelise the benefits of eliminating the data literacy gap. Closing the gap will allow you to harvest your organisation’s latent business value and benefit from the ongoing developments in data culture.
Why Bias and context is important to make data-informed decisions?
Having relevant, available data is not enough to make data-informed decisions. Decision-makers must also have an understanding of bias and context.
Decision-makers need to have a clear objective and follow where the data is pointing, instead of where they want it to take them. Developing awareness of what biases are at work when entering the decision-making process is the first step towards mitigating them. In communication, this means listening to ideas and giving them a ‘fair trial’, even if they go against the decision maker’s own ideals and beliefs.
Data must be communicated in context. Data might be available, but that does not mean it’s relevant to the decision making process at hand. Being able to select relevant data, and to apply it to the problem is essential.
Being aware of communicating data in context and the biases that can influence decision-makers and everyone involved in data collection and analysis will allow an organisation to benefit from and get the most out of data-informed decision making.
The Importance of Being Data Literate – Ted Talk
Jordan Morrow explains the importance of being data literate through his very own Ted talk!
Additional Articles on Data Literacy
Qlik-Launches-Data-Literacy-2-0-to-Drive-Data-Fluency-in-the-Enterprise. – Qlik
data-literacy-helping-non-data-specialists-make-the-most-of-data-science – UK Gov
Why data literacy is important in any business – Bernard Marr
Gartner clients can read more in the full reports Information as a Second Language: Enabling Data Literacy for Digital Society and
Toolkit: Enabling Data Literacy and Information as a Second Language by Valerie Logan, et al.
More information on the future of data and analytics can be found in the Gartner Featured Insight research collection “The Future of Data and Analytics,” a collection of research that explores new strategies, guidance and best practices across the data and analytics spectrum.
Become Data Literate in 3 Simple Steps – Data Journalism
Data Literacy A critical skill for the 21st century – Weather example (which in itself is misleading as at no point is the reader advised the forecast is for a period of 24hrs.
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